Acta Optica Sinica, Volume. 39, Issue 11, 1111001(2019)

Image Defocus Simulation Technology Applied to Evaluation of Focused Morphology Recovery Algorithm

Hao Wei1,2, Haihua Cui1,2、*, Xiaosheng Cheng1,2, and Xiaodi Zhang1,2
Author Affiliations
  • 1College of Mechanical and Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, Jiangsu 210016, China
  • 2Research Center of Digital Design and Manufacturing Engineering Technology of Jiangsu Province, Nanjing, Jiangsu 210016, China
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    To improve the reconstruction accuracy of the focused morphology recovery technique and find the optimal focused morphology recovery algorithm, a simulation technology of image defocus is proposed in this paper, which is used to assess the reconstruction accuracy of the focused morphology recovery algorithm. A three-dimensional model is conducted and a texture image is selected. Then, the uniformly-spaced point sampling on the model surface according to the image resolution is performed and organized point clouds are generated. The acquired data obtained through point sampling is processed and the texture is mapped. At last, a set of sequence simulation images which contain the ideal image or images with noises are generated. The sequence images are used to verify the focused morphology recovery algorithm in experiments. The reconstructed depth data and the actual depth data are compared to accurately evaluate the performance of the proposed algorithm. The research results demonstrate that the image defocus simulation can assess the performance of the focused morphology recovery algorithm effectively and provide further support to find more algorithms with higher stability and accuracy.

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    Hao Wei, Haihua Cui, Xiaosheng Cheng, Xiaodi Zhang. Image Defocus Simulation Technology Applied to Evaluation of Focused Morphology Recovery Algorithm[J]. Acta Optica Sinica, 2019, 39(11): 1111001

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    Paper Information

    Category: Imaging Systems

    Received: Apr. 8, 2019

    Accepted: Jul. 24, 2019

    Published Online: Nov. 6, 2019

    The Author Email: Cui Haihua (cuihh@nuaa.edu.cn)

    DOI:10.3788/AOS201939.1111001

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